Meteorological parameters are important variables, which influence the microclimate of a region. In the present study various climatic parameters i.e., rainfall, relative humidity, soil temperature, wind velocity, wind direction, dry bulb temperature, wet bulb temperature, maximum temperature, minimum temperature and pan evaporation are used to evaluate the interrelationship of these climatic variables using regression model based on 35 years of weather data recorded at Ranchi (23°23'N, 85°23'E and alt. 610 m), the capital of Jharkhand state. Statistical analysis was carried out using Microstat software employing correlation and regression equation (stepwise and linear regression). Using the correlation coefficient, and significant correlations between parameters, the regression equations have been developed with one dependent parameter and one or more independent parameters. Regression equations were subsequently used to validate regression model using the derived parameters and observed data. It has been established that interrelationship of climatic variables can be evaluated accurately using regression models.
Correlation matrix, Linear, Meteorological parameters, Stepwise regression model
